ADK Developer
A comprehensive guide and reference for building, orchestrating, and deploying AI agents using the Google Agent Development Kit (ADK).
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
462 skills found
A comprehensive guide and reference for building, orchestrating, and deploying AI agents using the Google Agent Development Kit (ADK).
Implement ReasoningBank adaptive learning with AgentDB's ultra-fast vector backend. Features trajectory tracking, verdict judgment, memory distillation, and pattern recognition for self-learning autonomous agents.
Development guide for Arma Reforger EnforceScript, covering component architecture, network replication, persistence, and memory management.
Universal media processing agent skill for converting, compressing, trimming, and editing audio/video files using FFmpeg.
Diagnose and resolve connection, sync, subscription, and type issues in Dojo.js applications. Use for troubleshooting Torii, entity queries, and state updates.
Symbol-level code understanding and navigation agent toolkit using LSP for precise code analysis, reference tracking, and surgical refactoring across 30+ programming languages.
Perform comprehensive technical analysis for stocks and ETFs using indicators like RSI, MACD, and Bollinger Bands to generate actionable trading signals and comparative reports.
Implement robust backend error handling with custom classes, middleware, structured logging, and recovery patterns.
Expert Solana Anchor development: build programs, manage PDAs, implement SPL tokens, handle security audits, and perform fuzz testing with Trident.
P9 Tech Lead mode: Manages P8 agent teams via Task Prompts (six-element) without direct coding. Orchestrates 3+ parallel agents for project management, task decomposition, and architecture.
Automated single-cell RNA-seq quality control pipeline following scverse best practices. Performs MAD-based outlier detection, cell filtering, and diagnostic visualization for .h5ad and .h5 datasets.
Analyze periodic signals in unevenly sampled astronomical time series data using the Lomb-Scargle periodogram method with the lightkurve library.